Publications of Sylvie Vanderick
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See detailAssessing animal welfare: Deriving individual welfare phenotypes from existing milk recording data
Franceschini, Sébastien ULiege; Leblois, Julie ULiege; Lepot, F. et al

Poster (2020, June)

Animal welfare is an increasing concern in dairy production. Consumers want an ethical production while farmers want to ensure the health of the animals. Animal welfare measurements at the herd level such ... [more ▼]

Animal welfare is an increasing concern in dairy production. Consumers want an ethical production while farmers want to ensure the health of the animals. Animal welfare measurements at the herd level such as the Welfare Quality® (WQ®) Protocol already exist but are time-consuming and costly. Moreover, assessing the overall well-being at the animal level becomes a challenge as herd measures for welfare can not be directly translated to the animal level. Two projects, active in the Walloon Region of Belgium, HappyMoo (Interreg NWE) and ScorWelCow, are trying to define individual welfare scores (IWS) and their prediction from routinely measured milk recording data, including mid-infrared spectral data representing fine milk composition. Data from WQ® Protocol and routine milk recording was collected during the same timeframe in 18 dairy farms with 1386 cows, the majority being genotyped. Two approaches to assess and to predict individual animal welfare were developed. The first approach consisted of two steps: translating the WQ® principles into IWS and predicting these from milk recording data. The variation observed in the first step while regressing WQ® animal measures on WQ® principles was considered representative of the biological variation between cows. IWS prediction Partial Least Square regression for the 4 principles of the welfare quality scores have R2 between 0.65 and 0.77. Moreover, results from this first approach showed a significant welfare assessor effect suggesting that welfare measurements were strongly human interpretation-dependent. This suggested the need for an alternative approach. The second approach directly used milk recording data such as spectral data to cluster cows in different groups, bypassing a priori definition of welfare by WQ®. Those groups were compared to results from the first approach and showed possible discrimination for herds with enhanced WQ® score ( Specificity = 1.00 but Sensitivity = 0.10) thus suggesting further unsupervised analysis. Based on this research, novel individual welfare traits could be developed allowing future genomic selection for improved welfare. [less ▲]

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See detailPedigree relatedness and pseudo-phenotypes as a first approach to assess and maintain genetic diversity of the Walloon Piétrain pig population
Wilmot, Hélène ULiege; REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege et al

in Livestock Science (2020), 233

The breeding of pure Piétrain animals is currently performed in two different contexts: industrial lines and individual breeders. As one of the four main pig breeds worldwide, the Piétrain breed might not ... [more ▼]

The breeding of pure Piétrain animals is currently performed in two different contexts: industrial lines and individual breeders. As one of the four main pig breeds worldwide, the Piétrain breed might not be considered to be endangered. However, in Wallonia (southern Belgium), even though the Belgian Piétrain programme aims to preserve the Walloon Piétrain population through cryopreservation of semen of relevant boars, only 10 pure Piétrain breeders remain and produce traditional breeding stock. Current breeders are retiring and no new breeders are replacing them. Moreover, the genetic diversity of the pigs from these individual breeders may highly contribute to the global gene pool of the breed, therefore it is important to assess this diversity. This was done on a local level by using pedigree relatedness but also differences in phenotypes. Pedigree parameters such as effective population size, genetic diversity and inbreeding coefficients were estimated for 219 boars from which offspring performances were recorded at the Walloon test station. A multi-dimensional scaling (MDS) was performed based on genetic distances. Considering the current owners of the boars, a principal component analysis (PCA) was made on deregressed breeding values (pseudo-phenotypes) based on the performances of their crossbred offspring at the test station. The effective population size was 223, the genetic diversity parameter was 97.96%, while the mean inbreeding coefficient was 2.74%. The MDS identified four main clusters of boars. Two principal components indicated two major directions of selection: growth or meat traits. Genetically close boars did not necessarily show similar performances in their offspring. Different performances for genetically linked animals should reflect the breeding objectives of their owner, a practice that was confirmed by most owners during interviews. Pedigree, phenotypes and genotypes provide complementary information and therefore should be used simultaneously in the implementation of conservation programmes. These first results also showed that the genetic diversity of the Walloon Piétrain population is so far well preserved. However, recommendations need to be developed in order to maintain it. For example, boars provided to the progeny-testing scheme should come from equally contributing breeders, allowing the Belgian Piétrain programme to sample boars from a larger variety of animals taking into account genetic and phenotypic diversity. Finally, in-situ preservation of Piétrain diversity will require the development of new tools and mating schemes. [less ▲]

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See detailPredicting milk mid-infrared spectra from first parity Holstein cows using a test-day mixed model with the perspective of herd management
Delhez, Pauline ULiege; Colinet, Frédéric ULiege; Vanderick, Sylvie ULiege et al

in Journal of Dairy Science (2020)

The use of test-day models to model milk mid-infrared (MIR) spectra for genetic purposes has already been explored; however, little attention has been given to their use to predict milk MIR spectra for ... [more ▼]

The use of test-day models to model milk mid-infrared (MIR) spectra for genetic purposes has already been explored; however, little attention has been given to their use to predict milk MIR spectra for management purposes. The aim of this paper was to study the ability of a test-day mixed model to predict milk MIR spectra for management purposes. A data set containing 467,496 test-day observations from 53,781 Holstein dairy cows in first lactation was used for model building. Principal component analysis was implemented on the selected 311 MIR spectral wavenumbers to reduce the number of traits for modeling; 12 principal components (PC) were retained, explaining approximately 96% of the total spectral variation. Each of the retained PC was modeled using a single trait test-day mixed model. The model solutions were used to compute the predicted scores of each PC, followed by a back-transformation to obtain the 311 predicted MIR spectral wavenumbers. Four new data sets, containing altogether 122,032 records, were used to test the ability of the model to predict milk MIR spectra in 4 distinct scenarios with different levels of information about the cows. The average correlation between observed and predicted values of each spectral wavenumber was 0.85 for the modeling data set and ranged from 0.36 to 0.62 for the scenarios. Correlations between milk fat, protein, and lactose contents predicted from the observed spectra and from the modeled spectra ranged from 0.83 to 0.89 for the modeling set and from 0.32 to 0.73 for the scenarios. Our results demonstrated a moderate but promising ability to predict milk MIR spectra using a test-day mixed model. Current and future MIR traits prediction equations could be applied on the modeled spectra to predict all MIR traits in different situations instead of developing one test-day model separately for each trait. Modeling MIR spectra would benefit farmers for cow and herd management, for instance through prediction of future records or comparison between observed and expected wavenumbers or MIR traits for the detection of health and management problems. Potential resulting tools could be incorporated into milk recording systems. [less ▲]

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See detailDoes the Walloon Piétrain pig breed require preservation measures?
Wilmot, Hélène ULiege; Vanderick, Sylvie ULiege; REIS MOTA, Rodrigo ULiege et al

in Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science (2019, August)

Piétrain pigs are used worldwide as terminal sires, and they are not expected to require preservation measures. However, the number of pure Piétrain breeders is dwindling everywhere and also in Wallonia ... [more ▼]

Piétrain pigs are used worldwide as terminal sires, and they are not expected to require preservation measures. However, the number of pure Piétrain breeders is dwindling everywhere and also in Wallonia (southern Belgium), the region where the breed is originated from. As a first step, the objective of this study was to assess the genetic diversity in Walloon Piétrain pig populations by using pedigree information. A total of 199 boars, whose breeders could be identified and which passed through performances testing using crossbred progeny at the performances recording station during the last ten years, were used for pedigree extraction. Kinship coefficients were determined and a classical multi-dimensional scaling (MDS) was performed on those boars for herd comparison purposes. In addition, breeders who have stopped their activity were identified in order to check genetic diversity loss overtime. Four groups were identified: a first cluster of Walloon Brabant breeders; a second core cluster, which suggests high levels of inbreeding, composed mainly by Hainaut breeders; a third cluster with great diversity, represented by a breeder whose animals may had German boars influence; and the last cluster formed by two breeders. The breeders from all four clusters are in ongoing pig breeding activities. However, due to their aging as well as the lack of new breeders, conservation measures establishment may be urgent in order to preserve genetic resources. As Walloon Piétrain breeders tend to keep very different phenotypes, complementary principal components analysis will be performed by using pseudo-phenotypes, by using deregressed estimated breeding values (EBV), to be compared with previous MDS results. Finally, single nucleotide polymorphisms (SNP) markers from different European Piétrain pig populations will be used to determine genomic relationships to further verify if Walloon Piétrain population(s) have intrinsic particularities, which would justify conservation measure [less ▲]

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See detailChromosome regions affecting MIR spectra indirect predictors of cheese-making properties in cattle
REIS MOTA, Rodrigo ULiege; Hammami, Hedi ULiege; Vanderick, Sylvie ULiege et al

in Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science (2019, August)

The current study aimed to identify single nucleotide polymorphism (SNP) markers and candidate genes associated with titratable acidity (TA), total caseins (TC) and dry cheese yield (DC) predicted from ... [more ▼]

The current study aimed to identify single nucleotide polymorphism (SNP) markers and candidate genes associated with titratable acidity (TA), total caseins (TC) and dry cheese yield (DC) predicted from MIR spectra as indirect predictors of milk cheese-making properties in early lactation cows. These predicted MIR novel phenotypes were obtained by using equations developed through GplusE and former EU projects. Only autosomes SNPs (n=29) with call rates >0.95, minor allele frequencies (MAF) >0.05 and significant deviations from Hardy-Weinberg equilibrium (P>10-7) were used for the genome-wide association study. After quality control edits, 32,687 SNPs remained for further analysis. The detection of SNPs affecting TA, TC and DC were obtained based on the proportion of variation explained by each SNP. The SNPs were considered as outliers if the proportion of variance explained was higher than 5×IQR+Q3, where IQR is the interquartile range and Q3 is the third quartile of the distribution. The putative genes located within or close to an outlier SNP were further identified. A total of 1,109 SNPs were considered as outliers with 8, 13, and 4% in common to all, between TC and DC, and between TC and TA traits, respectively. The remaining 833 were trait specific SNPs, with 18, 28, and 29% affecting TC, TA and DC, respectively. The 84 common SNPs to all traits were identified on BTA14 (75%), 1 (19%), 19 (5%) and 6 (1%). The trait specific markers were located on 26 out of 29 chromosomes. For TA, 86% of SNPs were located on chromosomes 1, 20, 7, and 14. On the other hand, TC showed the majority of SNPs on BTA6, BTA20 and BTA10 whereas for DC, SNPs were mainly on BTA5, BTA14 and BTA27. The top 5% outlier SNPs were located on BTA14, BTA1 and BTA20 with 20 (RPL8; FOXH1; CYHR1; OPLAH; HSF1; CPSF1; DGAT1; CYC1; GRINA; PARP10; NRBP2; PUF60; RNF19A; RRM2B; C8orf33; FBXO43; LY6H; ANKRD46; NAPRT; LY6E), 11 (FAM3B; MX1; HSF2BP; RRP1B; CSTB; C21orf2; LRRC3; DSCAM; ADARB1; ITGB2; MX2) and 3 (ANKH; TRIO; OTULIN) potential candidate genes affecting MIR indirect predictors (TA, TC and DC) of cheese-making properties in early lactation, respectively. [less ▲]

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See detailUsing milk MIR spectra to identify candidate genes associated with climate-smart traits in cattle
Hammami, Hedi ULiege; REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege et al

in Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science (2019, August)

Enhancing the resilience to extreme climate events and reducing greenhouse gases (mitigation), while improving productivity are of large importance in future breeding objectives. However, gaps to get ... [more ▼]

Enhancing the resilience to extreme climate events and reducing greenhouse gases (mitigation), while improving productivity are of large importance in future breeding objectives. However, gaps to get large-scale phenotyping as well as limited knowledge about the biological basis are still challenges. This study tried to exploit the milk MIR spectra jointly with genomics to identify potential candidate genes affecting mitigation and resilience abilities. For mitigation, methane emissions (CH4) and phosphorus (P) could be viewed as major sources of environmental pollution. Biomarkers reflecting the equilibrium between mobilisation and intake and body ketones associated with energy status are potential indicator traits for resilience to thermal stress. Predicted phenotypes form MIR data, CH4 and P (mitigation), and C18:1cis-9, Acetone, BHB in addition to milk yield (resilience) were used in this study. The proportion of variance explained by SNPs was evaluated for all studied traits. The putative genes located within or close to outliers SNPs were further identified. Concerning CH4 and P, 31; 28 and 7% of the what we called outliers SNPs were located at BTA14; BTA1 and BTA15, respectively. The markers in the most informative windows on BTA1 were close or within several genes such as RIPK4, PRDM15, ABCG1, SLC37A1, UBASH3A and FAM3B. On BTA14, the top outlier SNPs were located in LD block containing 3 genes (DGAT1, CYHR1, and PLEC). For resilience traits, the two outlier markers associated with acetone slope were located on BTA7 at approximately 45.5-45.7 Mb. Possible candidate genes located within this interval are UQC411 and ATP5F1D. The SNPs ARSBFGL- NGS-4939 and ARS-BFGL-NGS-34135, located on BTA14 were top SNPs and were also detected to affect milk, C18:1cis9, acetone, and BHB slopes. Interesting candidate genes such as DGAT1, HSP1 and SLC52A2 were identified surrounding those two markers. In conclusion, markers identified for resilience and mitigation traits could prove useful in genomic selection for climate-smart breeding programs. [less ▲]

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See detailStrategy to stabilize genomic breeding values under an evolving sire and cow reference population in the single-step evaluation system of Walloon region of Belgium
REIS MOTA, Rodrigo ULiege; Nader, S.; Vanderick, Sylvie ULiege et al

in Interbull Bulletin (2019), 55

The national genomic evaluations for production, conformation, udder health and functional traits in Wallonia are official since 2015. Nearly all evaluated traits are submitted to Interbull three times a ... [more ▼]

The national genomic evaluations for production, conformation, udder health and functional traits in Wallonia are official since 2015. Nearly all evaluated traits are submitted to Interbull three times a year which give gaps of four months between official genomic estimated breeding values (GEBV). Generating reliable GEBV is a major challenge. With our small population, changes in the reference population size can be extremely important. Currently, approximately 12 000 Holstein genotypes are available, with 8 500 being actually used in the evaluations. However, through projects and intensive testing an increase of at least 20% per year is expected. The question is now how can we stabilize GEBV when the reference population is constantly moving? This research here is associated to the derivation of an interim computational method intended to help breeders to make early decisions. This implementation consisted in: GEBV partition into polygenic (PT) and direct genomic (DGV) values; SNP effect estimation from DGV; GEBV prediction for new animals by combining DGV generated from SNP effects and PT. We also investigated the hypothesis that a core group of animals would be sufficient to estimate GEBV for other non-reference animals. To test this, a list of 648 genotyped animals having official GEBV from the last run was used as validation. Interim GEBVs were generated (by summing up PT, DGV and mean trait), and correlated with their official GEBV. Correlations between official and interim GEBVs were 0.92, 0.93, 0.93, 0.93, 0.94, 0.91, 0.91, 0.94 and 0.94 for milk yield, fat yield, fat percentage, protein yield, protein percentage, somatic cell score, longevity, direct calving ease and maternal calving ease, respectively. Relative mean differences were up to 6%. These results are a first indication that we could develop a stable reference population, generate high quality SNP effects and generate appropriate GEBV reflecting potentially own records for non-reference population animals. The last point is joint with efforts to generate appropriate reliabilities based on the approach promoted by Interbull. [less ▲]

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See detailExploiting opportunities in dairy cattle breeding using midinfrared spectral data associated to novel traits in the Walloon Region of Belgium
Gengler, Nicolas ULiege; Soyeurt, Hélène ULiege; Bastin, Catherine et al

in Interbull Bulletin (2019), 55

The Walloon Region of Belgium has started very early (since 2005) to collect mid-infrared (MIR) milk spectral data produced during routine milk performance recording by Dairy Herd Improvement (DHI ... [more ▼]

The Walloon Region of Belgium has started very early (since 2005) to collect mid-infrared (MIR) milk spectral data produced during routine milk performance recording by Dairy Herd Improvement (DHI) organizations and to research the possibilities offered by this technology. Already in 2008, a Walloon Research and Development (R&D) consortium was created. This partnership developed a framework to collect, to store, to research and to use milk MIR spectral data first from DHI, later from milk payment. This strategy was internationalized and related innovative “open” calibration schemes were developed. New international partners can benefit from this expertise. In order to get appropriate scientific and industry impacts, several major advances were achieved, the three most important being: 1) common strategies and specifications to access milk MIR data on many spectrometers from different laboratories and countries, to store and use this data; 2) standardization of MIR data across different spectrometers overtime to generate harmonized MIR data (i.e., organized through an international network); 3) making different, often heterogeneous, reference data useful for the development of novel calibration equations. In this “open” calibration strategy, partners get access to the latest version of the prediction equations and updates when new partners join, still retaining full control and confidentiality of their data, only the calibration equation building organizations have access to all data restricted to its use for equation building. We will present opportunities and challenges for two groups of MIR based traits, fatty acids and methane emission proxy traits in dairy cattle breeding. Similarly, R&D are ongoing for the use of MIR data for many other traits as milk and milk product (i.e., cheese making) quality, animal efficiency and resilience, health and welfare traits (e.g., resistance to heat stress) to be used in future genomic evaluations. We have experienced that there are countless opportunities in MIR based breeding, only restricted by the limits in financial and human resources available in the Walloon Region. [less ▲]

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See detailAdditional considerations to the use of single-step genomic predictions in a dominance setting
REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

in Journal of Animal Breeding and Genetics (2019), 136(6), 430-440

Recent publications indicate that single-step models are suitable to estimate breeding values, dominance deviations and total genetic values with acceptable quality. Additive single-step methods ... [more ▼]

Recent publications indicate that single-step models are suitable to estimate breeding values, dominance deviations and total genetic values with acceptable quality. Additive single-step methods implicitly extend known number of allele information from genotyped to non-genotyped animals. This theory is well derived in an additive setting. It was recently shown, at least empirically, that this basic strategy can be extended to dominance with reasonable prediction quality. Our study addressed two additional issues. It illustrated the theoretical basis for extension and validated genomic predictions to dominance based on single-step genomic best linear unbiased prediction theory. This development was then extended to include inbreeding into dominance relationships, which is a currently not yet solved issue. Different parametrizations of dominance relationship matrices were proposed. Five dominance single-step inverse matrices were tested and described as C1, C2, C3, C4 and C5. Genotypes were simulated for a real pig population (n = 11,943 animals). In order to avoid any confounding issues with additive effects, pseudo-records including only dominance deviations and residuals were simulated. SNP effects of heterozygous genotypes were summed up to generate true dominance deviations. We added random noise to those values and used them as phenotypes. Accuracy was defined as correlation between true and predicted dominance deviations. We conducted five replicates and estimated accuracies in three sets: between all (S1), non-genotyped (S2) and inbred non-genotyped (S3) animals. Potential bias was assessed by regressing true dominance deviations on predicted values. Matrices accounting for inbreeding (C3, C4 and C5) best fit. Accuracies were on average 0.77, 0.40 and 0.46 in S1, S2 and S3, respectively. In addition, C3, C4 and C5 scenarios have shown better accuracies than C1 and C2, and dominance deviations were less biased. Better matrix compatibility (accuracy and bias) was observed by re-scaling diagonal elements to 1 minus the inbreeding coefficient (C5). [less ▲]

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See detailLinking first lactation survival to milk yield and components and lactation persistency in Tunisian Holstein cows
Grayaa, Marwa ULiege; Vanderick, Sylvie ULiege; Rekik, Boulbaba et al

in Archiv für Tierzucht (2019), 65(1), 153160

Genetic parameters were estimated for first lactation survival defined as a binary trait (alive or dead to second calving) and the curve shape traits of milk yield, fat and protein percentages using ... [more ▼]

Genetic parameters were estimated for first lactation survival defined as a binary trait (alive or dead to second calving) and the curve shape traits of milk yield, fat and protein percentages using information from 25 981 primiparous Tunisian Holsteins. For each trait, shape curves (i.e. peak lactation, persistency), level of production adjusted to 305 days in milk (DIMs) for total milk yield (TMY), and average fat (TF %) and protein (TP %) percentages were defined. Variance components were estimated with a linear random regression model under three bivariate animal models. Production traits were modelled by fixed herd × test-day (TD) interaction effects, fixed classes of 25 DIMs × age of calving × season of calving interaction effects, fixed classes of pregnancy, random environment effects and random additive genetic effects. Survival was modelled by fixed herd × year of calving interaction effects and age of calving × season of calving interaction effects, random permanent environment effects, and random additive genetic effects. Heritability (h2) estimates were 0.03 (±0.01) for survival and 0.23 (±0.01), 0.31 (±0.01) and 0.31 (±0.01) for TMY, TF % and TP %, respectively. Genetic correlations between survival and TMY, TF % and TP % were 0.26 (±0.08), −0.24 (±0.06) and −0.13 (±0.06), respectively. Genetic correlations between survival and persistency for fat and protein percentages were −0.35 (±0.09) and −0.19 (±0.09), respectively. Cows that had higher persistencies for fat and protein percentages were more likely not to survive. [less ▲]

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See detailTemporal relationship between milk MIR predicted metabolic disorders and lameness events
Mineur, Axelle ULiege; Vanderick, Sylvie ULiege; Hammami, Hedi ULiege et al

in Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science (2018, August 27)

Lameness is an often occurring consequence of various metabolic disorders, such as sub-acute ruminal acidosis (SARA) or ketosis. Recent research showed that these metabolic disorders can be predicted with ... [more ▼]

Lameness is an often occurring consequence of various metabolic disorders, such as sub-acute ruminal acidosis (SARA) or ketosis. Recent research showed that these metabolic disorders can be predicted with reasonable accuracy with mid-infrared (MIR) spectral data. In order to study the potentially complex temporal relationship between MIR predicted metabolic disorders and lameness events over the course of the lactation, data from 3895 cows on 122 farms, representing the Simmental, Brown-Swiss and Holstein breeds. A total of 38316 lameness and 11419 MIR records were collected over a period from July to December 2014 through the Efficient Cow Project. Lactations were subdivided into 30 days lactation stage classes. Milk MIR predicted metabolites such as ketone bodies, acetone, citrates and fatty acids (C18:1cis9), and lameness scores were averaged over animals and these classes. In order to assess the temporal link between occurrences of metabolic disorder and lameness events, correlations were computed between averaged metabolites and lameness scores across the lactation stage classes. Correlations tended to be higher when comparing predicted metabolites with lameness in the three following months, rather than the same one. Results showed differences between breeds, Simmentals showing lower correlations than Holsteins or Brown-Swiss. Especially very early values for milk MIR predicted metabolites (first month), and therefore suspected metabolic disorders, were correlated more strongly to later occurring lameness events in Brown Swiss. In Holsteins, higher correlation between metabolites and lameness were observed during later lactation. In general, given the use of classes, the correlations tended to be unstable. Alternative methods, such as covariance functions, might therefore be useful to get a clearer picture. However these first results seem to support the idea of temporal relationships between metabolic disorders and later lameness events during the lactation. [less ▲]

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See detailIdeas for continuous genomic evaluation for newly genotyped Walloon Holstein females and males
Naderi Darbaghshahi, Saeid ULiege; REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Crucial for large scale use in dairy cattle of genotyping for females is that any newly genotyped animal (calves, cows and heifers but also bulls) receives very quickly genomic breeding values (GEBV) even ... [more ▼]

Crucial for large scale use in dairy cattle of genotyping for females is that any newly genotyped animal (calves, cows and heifers but also bulls) receives very quickly genomic breeding values (GEBV) even outside the official schedule for routine evaluations. In this study, a system was developed to estimate initial GEBV for newly genotyped animals before their inclusion in the official routine release of genomic evaluations. The system was setup to be run on request, featuring the setup of a ‘continuous’ evaluation, also being quick and simple enough to be used at least on a weekly base. For animals without own records or descendants, official GEBV were approximated using selection-index like method by combining direct genomic values (DGV) of newly genotyped animals and their parent average (PA). DGV for new genotyped animals were calculated based on SNP effects from the previous official routine evaluations (April and August, 2017). Depending on GEBV accessibility from parents of a given animal, PA was calculated based on conventional phenotypic information (cPA), and parent GEBV (gPA). To expand the system for animals with progeny, a subset of genotyped animals was selected, and conventional estimated breeding values (cEBV) and cPA of selected animals were combined with DGV and gPA in order to obtain GEBV for animals with progeny. The weights were calculated based on the covariance between DGV and gPA for animals without progeny, and between DGV, gPA, cEBV and cPA for animals with progeny. Correlations between initial and April official evaluations for 60 new genotyped animals without progeny varied from 0.87 to 0.95 for conformation, fertility and production traits, whereas correlations between initial and August official evaluations varied 0.84 to 0.92 (n=25 new genotyped animals). On the other hand, correlations between initial and August official evaluations for 120 genotyped animals with progeny varied from 0.95 to 0.97 for production traits. Study showed potential to use simple selection index based methods in continuous genomic evaluations, a way to support genotyping of females for genomic selection but also for management and marketing. [less ▲]

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See detailPrediction of milk mid-infrared spectrum using mixed test-day models
Delhez, Pauline ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

Conference (2018, August)

Mid-infrared (MIR) analysis of milk currently allows the measurement of many variables of interest for the dairy sector related to milk nutritional quality, milk technological properties, cow’s status or ... [more ▼]

Mid-infrared (MIR) analysis of milk currently allows the measurement of many variables of interest for the dairy sector related to milk nutritional quality, milk technological properties, cow’s status or environmental fingerprint. The aim of this study was to explore the ability of a test-day model to predict milk MIR spectra, and therefore all the resultant variables, for a future test day of a known cow or for a new cow based on easily known characteristics of cows. This is useful for instance for herd management (e.g. detecting problems, predicting potential of heifers) or to predict future environmental impacts of a dairy herd. A total of 467,496 milk MIR spectra from 53,781 Holstein cows in first lactation were used for the calibration data set. First, 323 wavelengths out of the 1,060 wavelengths of the milk spectra were conserved. This spectral information was reduced by using principal component analysis (PCA). A total of 8 principal components (PC) were kept, representing 99% of the spectral information. Then 8 univariate test-day models including the day in milk, herd×year and herd×month as fixed effects and herd×test date, permanent environment and genetics as random effects were applied for each PC. From the solutions of the models and by using a back reversing operation using eigenvectors of the PCA, the predicted 323 wavelengths of the spectra were re-obtained. The calibration correlations between observed and predicted spectral data ranged from 0.76 to 0.93. Correlations between observed and predicted milk fat and protein contents obtained from the modelled spectra were 0.83 and 0.89, respectively. These findings demonstrate the moderate ability of a test-day model to predict milk MIR spectra. [less ▲]

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See detailGenetic parameters of novel mid-infrared predicted milk traits in three dual-purpose cattle breeds
Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege; Mineur, Axelle ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

The objective of this study was to estimate genetic parameters of 39 novel mid-infrared predicted milk traits (e.g. nutritional quality, technological properties, metabolic status, environmental ... [more ▼]

The objective of this study was to estimate genetic parameters of 39 novel mid-infrared predicted milk traits (e.g. nutritional quality, technological properties, metabolic status, environmental fingerprint) for three dual purpose cattle breeds (i.e. Dual-Purpose Belgian Blue (dpBB), Montbéliarde (MON) and Normande (NOR)), which are also used in organic farming in the Walloon Region of Belgium, as part of the 2-Org-Cows project. Edited data included 21,287, 10,062 and 4,637 first-lactation test-day records collected in the Walloon region of Belgium from 2,988, 1,330 and 621 dpBB, MON and NOR cows, respectively. Genetic parameters were estimated using REML applied to single-trait random regression test-day models for six conventional traits (yields, contents and somatic cell score) and the 39 novel mid-infrared predicted milk traits. Results for conventional traits allowed comparison to literature showing values that were close to the expected ones. For novel traits, comparison with available literature values for Holstein breed showed generally similar estimated heritabilities. Reported average daily heritabilities estimated for the 39 novel traits tended to be higher for dpBB (0.13-0.64) than MON and NOR (0.03-0.60) breeds. Few novel traits showed large differences between breeds except between dpBB and NOR for milk composition traits. However, results for NOR breed have to be taken very carefully given the low number of animals. Even if the used methane prediction equation was not yet validated for these breeds, estimated average daily heritability was moderately high for dpBB (0.41) and MON (0.36) and moderate for NOR (0.23) indicating that this prediction might also be useful in these dual purpose breeds. [less ▲]

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See detailTheoretical basis to extend single-step genomic prediction of dominance in a pig population
REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Single-step methods predict implicitly unknown gene content information of non-genotyped from known gene content for genotyped animals. This theory is well derived in an additive setting. There are ... [more ▼]

Single-step methods predict implicitly unknown gene content information of non-genotyped from known gene content for genotyped animals. This theory is well derived in an additive setting. There are reasons not to ignore the dominance context when working with partially genotyped populations. This study addressed several outstanding issues in this context. First, it presented the theoretical basis for dominance single-step genomic best linear unbiased prediction theory. A specific and important issue in all dominance setting is the handling of inbreeding. A total of five dominance single-step inverse matrices were tested and described as C1 to C5 by considering different parameterization (e.g. different ways to account for inbreeding) for pedigree-based and genomic relationships matrices. We simulated genotypes for real crossbred pig population (n=11,943 animals). The SNP effects were assumed to be equal to calculate true dominance values. We added random noise and used them as phenotypes. Accuracy was defined as correlation between true and predicted dominance breeding values. We applied five replicates and estimated accuracies between three situations: all (S1); non-genotyped (S2) and inbred non-genotyped animals (S3). Potential bias of predicted dominance values was assessed by regressing the true dominance values on predicted values. Accuracies of each tested matrix (C1 to C5) were 0.75, 0.33 and 0.35 in average, for S1, S2 and S3, respectively. The matrix C5 better performed and breeding values from C1 and C2 were more biased than those obtained by using C3, C4 and C5. We showed a useful approach to predict dominance gene contents for nongenotyped from genotyped animals. Better matrix compatibility can be obtained by re-scaling the pedigree-based and the genomic relationship matrices to obtain standardized diagonal elements equal to 1 minus the inbreeding coefficient, i.e. the C5 matrix. [less ▲]

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See detailMulti-omics data integration approach for resilience of dairy cattle to heat stress
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Breeding for resilience to heat stress (HS) is a topic where associating multiple omics data has the potential to get a better view of the issues and to allow significant advances to overcome undesirable ... [more ▼]

Breeding for resilience to heat stress (HS) is a topic where associating multiple omics data has the potential to get a better view of the issues and to allow significant advances to overcome undesirable consequences of future extreme weather scenarios. An example of omics is here epigenomics (e.g. early programming due to heat-stress) allowing new insights to explain biological mechanisms of resilience to HS and G×E interactions. Even if biological mechanisms are complex and still elusive, this study tried to use a holistic approach integrating milk-based biomarkers, climate conditions, and genomics. Data used included 65,907 third-lactation test-day records for production traits (milk, fat and protein yields), specific fatty acids (FA) and metabolites predicted from mid-infrared spectra (C4:0, C18:1cis9, long chain ‘LCFA’, mono- and unsaturated FA ‘MUFA and UFA’, acetone and BHB) of 9,327 Holstein cows. Phenotypes were merged with a temperature humidity index (THI) from public weather stations. For each trait, the response to THI was estimated via days in milk (DIM) × THI combination, and for each cow by using a random regression model with a common threshold of THI=62. The slope (heat tolerance)-to-intercept (general) genetic variance ratios increased as THI increased. They were higher during mid-lactation (140-245 DIM) for C18:1 cis9, acetone, BHB and for production traits, whereas higher in early lactation (≤125 DIM) for C4:0, LCFA, MUFA, and UFA. At extreme high THI scale, slope-to-intercept ratios for C18:1 cis9, MUFA, UFA, and LCFA were 3.8, 3.4, 3.1, 2.8 fold higher than milk yield. These findings indicate that tolerance to HS and traditional production trait responses to THI are marginally related, and changes in milk-based biomarkers under high THI better elucidate physiological and metabolic pathways in HS dairy cows. Ongoing genomic wide association studies will better explain genetic markers unravelling the biological background of resilience to HS. [less ▲]

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See detailEarly-programming of dairy cattle, a potential explanation to the adaptation to climate change
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Breeding for robustness and considering genotype by environment interaction (G×E) is linked to adaptation. Recently, it has been established that gene expression can be affected by the environment during ... [more ▼]

Breeding for robustness and considering genotype by environment interaction (G×E) is linked to adaptation. Recently, it has been established that gene expression can be affected by the environment during the embryo development. The concept of early programming has been demonstrated in many settings. This study aimed to assess the impact of thermal stress when dairy cows been conceived on their lifetime performances. Studied traits were milk yield and some novel milk-based biomarkers, fertility (days open), health (somatic cell score and ketosis), and heat tolerance. Data used compromised 905,391 test day of 58,297 cows in parity 1 to 3 for production traits, health and ketosis status, 104,635 records of 48,125 cows for days open, and 399,449 test days recorded (linked with temperature humidity index values, THI) of 28,203 cows for heat tolerance trait. Date of conception was estimated using the next calving date of the cow and subtracting 280 d from the calving interval. Cows being conceived in summer (June- August) were considered as influenced by heat stress (environment 1) and those conceived in winter (December- February) as neutral-thermal conditions (environment 2). G×E was analysed by a multi-trait model for days open in which each of the 3 lactations measured in heat stress and thermo-neutral conditions were considered as separate traits. For the rest of the traits, it was analysed using reaction norm models, in which the trait is considered a function of an environmental descriptor (i.e. THI, days in milk) in the two discrete environments. First results showed that genetic correlations across both early-life defined environments and lactations were substantially lower than unity, implying that effects of genes for cows conceived under neutral-thermal conditions may be different of the effects for the same genes for cows conceived under heat stressed conditions. [less ▲]

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See detailEffect of milk yield and milk content curve shapes on first lactation survival in large herds
Grayaa, Marwa ULiege; Ben Gara, A.; Grayaa, S. et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Genetic parameters of first lactation survival and curve shape traits of milk yield, fat and protein percentages were estimated using information of 25,981 primiparous Tunisian Holsteins belonging to ... [more ▼]

Genetic parameters of first lactation survival and curve shape traits of milk yield, fat and protein percentages were estimated using information of 25,981 primiparous Tunisian Holsteins belonging to large herds. For each trait lactation peak, apparent persistency, real persistency and level of production adjusted to 305 days in milk were defined. Variance components were estimated under three bivariate animal models with a linear random regression model. Milk yield as well as fat and protein percentages were modelled by fixed herd × test day interaction effects, fixed classes of 25 days in milk × age of calving × season of calving interaction effects, random environment effects, and random additive genetic effects. Survival was modelled by fixed herd × year of calving interaction effects, age of calving × season of calving interaction effects, random environment permanent effects, and random additive genetic effects. Heritability estimates were 0.03 for survival, 0.23, 0.29 and 0.30 for average milk yield, fat and protein percentages adjusted to 305 days in milk, respectively. Genetic correlations between survival and average milk yield, fat and protein percentages adjusted to 305 days in milk were 0.33, -0.33 and -0.14, respectively. Genetic correlations between survival and real persistency for fat and protein percentages were -0.24 and -0.15, respectively. Cows that had higher persistencies for fat and protein percentages, and therefore flatter fat and protein percentages curves, were more likely not to survive. This was due to higher fat percentages at the end of the lactation leading to the hypothesis that cows producing higher fat percentage dispose of less energy available for gestation and were therefore less likely to be or remain pregnant and, therefore, to survive. [less ▲]

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See detailFirst study into the temporal relationship between metabolic disorders and lameness events over the course of a lactation
Mineur, Axelle ULiege; Egger-Danner, Christa; Sölkner, Johann et al

Conference (2018, June 25)

Lameness in dairy cows is an issue that can vary greatly in severity, and is of concern for both producers and consumers. Metabolic disorders are a major problem in themselves, and, next to this, can ... [more ▼]

Lameness in dairy cows is an issue that can vary greatly in severity, and is of concern for both producers and consumers. Metabolic disorders are a major problem in themselves, and, next to this, can cause lameness. Indeed, lameness is an often occurring consequence of various metabolic disorders, such as sub acute ruminal acidosis (SARA), ketosis or milk fever. The caused lameness event can occur weeks to months after the metabolic disorder making the detection of causality difficult. Moreover, detection of many metabolic disorders is very challenging and not straightforward. Mid-infrared (MIR) technology is already used for the prediction of major milk components, such as fat or protein, during routine milk recording and for milk payment. It was recently shown that this technology can also be used to predict novel components, linked to metabolic disorders of cows, such as ketone bodies, citrate and minerals. In the context of limiting the occurrence and severity of lameness, early prediction of lameness could help indicate the need to adapt the management and the environment of a cow at risk of lameness. Therefore, the aim of this study was to analyze the temporal link between metabolic disorders and lameness events, using locomotion scores of the cow and MIR based milk biomarkers for different metabolic disorders of her milk from previous test days. Data recorded between, July 2014 and December 2014, consisted of 9324 records, from 3895 cows and 122 farms. Correct definition of the response variable is an important aspect as extremes in lameness severity, expressed on lameness scales, were more easily predictable. First results were obtained using covariance functions on correlations computed between averaged metabolites and lameness scores, per animal, across the lactation stage classes. Correlations tended to be higher when comparing predicted metabolites with lameness in the three following months, rather than the same one, hinting at a temporal relationship. [less ▲]

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